1958-2017年太湖蒸发量年际变化趋势及主控因子

湖泊蒸发对气候变化非常敏感,是水文循环响应气候变化的指示因子,因此研究湖泊蒸发的控制因素,对于理解区域水文循环有重要意义.本文利用太湖中尺度涡度通量网避风港站观测数据校正JRA-55再分析资料,驱动CLM4.0-LISSS模型,并利用2012-2017年涡度相关通量数据和湖表面温度数据检验模型模拟蒸发结果,验证了该模型在太湖的适用性;估算了1958-2017年间太湖的湖面蒸发量,并利用Manner-Kendall趋势检验分析了湖面蒸发的变化趋势,寻找太湖实际蒸发的年际变化的主控因子.结果如下:校正后的JRA-55再分析资料模拟的太湖蒸发与观测值之间存在季节偏差,但是季节偏差在年尺度上相互抵消,再分析资料可用于年际尺度太湖蒸发变化的模拟;1958-2017年间太湖蒸发量以1977年为界,先下降(-3.6 mm/a),后增加(2.3 mm/a);多元逐步回归结果表明,向下的短波辐射是太湖1958-2017年间太湖蒸发变化的主控因子,向下的长波辐射、气温、比湿也对湖泊蒸发年际变化有一定影响,但是风速对蒸发量的年际变化影响不大.     

蓝色北极情景下西北太平洋台风会增多吗？

未来的全球变暖情景下,西北太平洋台风活动会有怎样的变化？利用CMIP3模式在IPCC AIB情景下对未来气候的预估结果,得到全球变暖之北极夏季（September）无海冰时的一种情景,即“蓝色北极”．利用相应的海温场和CO：含量驱动一个全球大气环流模式,来对北极夏季无海冰时的西北太平洋台风生成环境做出数值模拟．试验结果表明,蓝色北极情况下,6～10月西北太平洋的大气环流和海洋环流都发生了明显变化,影响台风活动的主要环境要素：纬向风垂直切变和向外射出长波辐射空间分布的变化分别有利于台风源地向偏西、偏北转变;与台风频数有密切联系的关键区中上述量的变化且皆利于台风频次的减少．热带气旋生成潜力指数的变化表现为西北太平洋东部减小,而西部增大．因而呈现了非常复杂的变化格局．     

一个改进的诊断层积云方案及其对大气环流模式性能的改进

在气候模式中,传统的层积云参数化方案(简称LTS方案)高估了自由大气湿绝热过程所引起的垂直温度梯度的作用.在Wood和Bretherton提出的"估算逆温"(EIS)基础上,本文基于卫星资料构建了一个改良的诊断层积云方案,旨在改进当前广为使用的LTS方案.通过将EIS层积云方案引入大气环流模式GAMIL2.0中,并与传统方案进行对比试验发现,EIS层积云方案能有效地改善GAMIL2.0对东亚-西北太平洋季风区乃至全球云-辐射气候特征的模拟能力,一定程度地纠正了模式原来存在的中高纬度净(短波)云辐射强迫模拟偏弱的现象,而该偏差在当前许多模式中普遍存在.此改进与EIS层积云方案合理处理自由大气的温度层结有关.EIS层积云方案亦显著改进了GAMIL2.0对东亚-西北太平洋季风区云辐射年际变率的模拟能力.加入EIS层积云方案后,模式较好地模拟出了ENSO年冬春季东亚边缘海域的净云辐射正异常、海表入射短波正异常和层云量负异常.究其原因是EIS层积云方案比传统方案对海表温度异常的扰动更敏感.海表温度异常通过EIS层积云方案在对流层低层强迫出更强的云量距平,并通过改变加热率和垂直速度影响整个对流层,最终改进模式对云辐射强迫和地表入射短波通量年际变率的模拟.EIS层积云方案还增强了模式对El Ni?o年冬春季节西北太平洋异常反气旋以及东亚降水异常的模拟效果.     

秋季北极海冰与欧亚冬季气温在年代际和年际尺度上的不同联系

北极海冰的急剧消融在近年来欧亚大陆频发的低温事件中扮演着关键角色.秋季北极海冰的偏少对应着冬季欧亚大陆的低温天气,然而二者的联系在年代际和年际两种时间尺度上存在显著区别.本文运用1979—2012年哈德莱中心第一套海冰覆盖率(HadISST1)、欧洲中心(ERA_Interim)的2m温度、风场、海平面气压场、高度场等资料,分别研究了年代际和年际时间尺度上前期秋季北极海冰与欧亚冬季气温的联系.结果表明,欧亚和北极地区(0°—160°E,15°N—90°N)的冬季气温具有显著的年代际和年际变化.在年代际尺度上,温度异常分布在21世纪初由北极冷-大陆暖转为北极暖-大陆冷.这一年代际转折与前期秋季整个北极地区的海冰年代际减少联系密切.秋季北极全区海冰年代际偏少对应冬季欧亚大陆中高纬地区的高压异常,有利于北大西洋的暖湿气流北上和北极的冷空气南侵,造成北极暖-大陆冷的温度分布;在年际时间尺度上,温度异常分布主要由第一模态的年际变化部分和第二模态组成,且第一模态包含的年际变率信号也存在显著的年代际变化.年际尺度上全区北极海冰对欧亚冬季气温的影响远不及位于北冰洋西南边缘的巴伦支海、喀拉海和拉普捷夫海西部(30°E—120°E,75°N—85°N)的关键区海冰影响显著.关键区内海冰的偏少会引发冬季的北大西洋涛动负位相,导致北大西洋吹往欧亚大陆的暖湿气流减弱和欧亚大陆中高纬地区的气温偏低.     

冬季大气斜压性对黑潮延伸体年代际异常响应的维持机制研究

黑潮延伸体(Kuroshio Extension,KE)海域附近具有强烈的大气斜压性可显著影响北太平洋上空风暴轴异常,因而有必要研究KE海区附近斜压性的特征和维持机制.本文设计数值试验并结合高分辨率ERA-Interim资料研究了大气斜压性对KE 年代际海温变率模态(KEDV-induced SSTA,Kuroshio...     

青藏高原单点陆面过程模拟试验

利用青藏铁路北麓河试验2002年6月的大气资料作为陆面模式的强迫场, 研究陆面过程模式(NCAR/LSM)在高原地区的模拟能力. 模拟结果表明, 在观测资料的强迫下, NCAR/LSM能够较好地模拟出地表特征量的变化趋势. 在LSM模式中青藏高原地区的地表植被类型描述与实况存在较大差异, 根据实际地表特征, 我们定义北麓河地区草原植被覆盖度为0.6, 叶冠高度为0.15, 位移高度为0.10. 通过对比试验发现, 修正模式参数后, 模拟的地面气温和地表温度日变化更接近于观测值, 对温度峰值模拟有较好改善. 地面通量模拟也有一定改善. 所以, 修正LSM模式中高原地区的地表及植被描述参数, 可以有效地提高陆面过程模式在青藏高原地区的模拟性能.     

FGOALS－g快速耦合模式模拟的北太平洋年代际变率

本文分析了由中国科学院大气物理研究所大气科学和地球流体力学数值模拟国家重点实验室（LASG/IAP）最新发展的FGOALS_－g快速耦合模式300 a积分模拟结果,通过与多种观测资料的对比分析,讨论了北太平洋年代际变率的时空结构、主要年代际模态的演变特征以及与ENSO的联系等研究内容. 结果表明：该模式能成功模拟出北太平洋年代际变率的主要空间分布特征;模拟的年代际模态具有多时间尺度性,其中最显著的是周期约为10～20 a左右的准20年振荡模态,该模态上层海洋热容量异常的演变过程主要表现为大致沿副热带海洋涡旋做海盆尺度顺时针旋转的特征,相应的大气异常不仅与阿留申低压的变异有关,而且与太平洋-北美PNA）遥相关型以及上游的欧亚大气环流异常有密切关系;模拟的北太平洋年代际变率对年际ENSO循环的发生频率和强度有明显的调制作用. 但模拟的KOE区和阿拉斯加湾SST异常振幅比观测偏强,这与模式海冰偏多、高纬度SST偏冷的误差有关.     

FGOALS－g快速耦合模式模拟的北太平洋年代际变率

本文分析了由中国科学院大气物理研究所大气科学和地球流体力学数值模拟国家重点实验室（LASG/IAP）最新发展的FGOALS_－g快速耦合模式300 a积分模拟结果,通过与多种观测资料的对比分析,讨论了北太平洋年代际变率的时空结构、主要年代际模态的演变特征以及与ENSO的联系等研究内容. 结果表明：该模式能成功模拟出北太平洋年代际变率的主要空间分布特征;模拟的年代际模态具有多时间尺度性,其中最显著的是周期约为10～20 a左右的准20年振荡模态,该模态上层海洋热容量异常的演变过程主要表现为大致沿副热带海洋涡旋做海盆尺度顺时针旋转的特征,相应的大气异常不仅与阿留申低压的变异有关,而且与太平洋-北美PNA）遥相关型以及上游的欧亚大气环流异常有密切关系;模拟的北太平洋年代际变率对年际ENSO循环的发生频率和强度有明显的调制作用. 但模拟的KOE区和阿拉斯加湾SST异常振幅比观测偏强,这与模式海冰偏多、高纬度SST偏冷的误差有关.     

北冰洋中心区夏季大气边界层结构特征及其与海冰范围变化的关系

利用中国第4~6次北极考察获得的北冰洋中心区(80°~88°N))GPS探空资料和NCEP再分析资料,分析了大气垂直结构、边界层参数的变化特征及其与海冰和温度变化的关系.结果表明,2010、2012和2014年夏季北冰洋中心区的对流层顶、边界层高度、逆温强度及风速和风向的垂直结构均存在明显差异.通过分析1979~2014年9月温度与海冰范围变化的关系,解释了其差异的原因.2012年9月北极海冰范围最小,减少了44%,具有明显的增温过程.2010年和2014海冰分别减少了22.6%和17%,出现的是降温过程.对比2种过程反映出海冰变化对大气边界层结构有重要影响.近30年北冰洋中心区(80°~90°N)1000和850hPa的温度变化呈显著的升温趋势,并与海冰范围呈显著的负相关.表明北极海冰的持续减少,会使地表至对流层中层持续增温.     

东亚地区矿物尘气溶胶直接辐射强迫的初步模拟研究

为研究东亚地区矿物尘气溶胶的直接辐射效应,在区域气候模式RegCM3中加入起尘方案、建立矿物尘气溶胶输送模式,并将其辐射过程加入区域气候模式的辐射方案.通过对2001年3月～2002年3月的模拟发现：中国西北和蒙古国年平均地表起尘率在1μg/(m2·s)以上,最大达到90μg/(m2·s)是东亚地区最主要的矿物尘气溶胶源地;东亚地区矿物尘气溶胶柱含量最大值达5g/m2,出现在塔克拉玛干沙漠和秦岭地区;气溶胶大气顶直接辐射强迫基本呈现大陆上为正、海洋上正负均有的分布特征,区域平均辐射强迫在春夏秋冬分别为108, 088, 037,040W/m2,短波辐射强迫在陆上为正、海上正负均有,长波辐射强迫均为正值;四季的地表辐射强迫分别为-564, -225, -137, -187W/m2;辐射强迫数值对矿物尘气溶胶单次散射反照率的变化较敏感.     

New satellite derived sea ice motion tracks Arctic contamination

Sea ice has been reported to contain contaminants from atmospheric and nearshore sediment resuspension processes. In this study successive passive microwave images from the 85.5 GHz channels on the Special Sensor Microwave Imager (SSM/I) were merged with drifting buoy trajectories from the International Arctic Buoy Program to compute Arctic sea ice motion in the Russian Arctic between 1988 and 1994. Smooth daily motion fields were averaged to prepare monthly maps making it possible to compute the 7-year mean and mean seasonal ice motions as well as principal components of directional variability of sea ice motion for the entire Arctic and surrounding basins. These mean motion vectors are used to simulate the advection of contaminants deposited on or contained within the sea ice and subsequently transported into the Arctic Ocean in order to predict both their mean trajectories and dispersal over time. The 3-year displacement of contaminants from a number of Russian sites and one American site display various behaviours from substantial displacement and dispersal to almost no movement. This computational procedure could be applied to realtime SSM/I and ice buoy data to provide detailed, all-weather, vector motion maps of ice circulation to predict the path and dispersal of any new substance introduced to the sea ice and transported into the Arctic or Antarctic ocean surface.     

Connection of sea level variability between the tropical western Pacific and the southern Indian Ocean during recent two decades

Based on the merged satellite altimeter data and in-situ observations,as well as a diagnosis of linear baroclinic Rossby wave solutions,this study analyzed the rapidly rise of sea level/sea surface height(SSH)in the tropical Pacific and Indian Oceans during recent two decades.Results show that the sea level rise signals in the tropical west Pacific and the southeast Indian Ocean are closely linked to each other through the pathways of oceanic waveguide within the Indonesian Seas in the form of thermocline adjustment.The sea level changes in the southeast Indian Ocean are strongly influenced by the low-frequency westward-propagating waves originated in the tropical Pacific,whereas those in the southwest Indian Ocean respond mainly to the local wind forcing.Analyses of the lead-lag correlation further reveal the different origins of interannual and interdecadal variabilities in the tropical Pacific.The interannual wave signals are dominated by the wind variability along the equatorial Pacific,which is associated with the El Ni?o-Southern Oscillation;whereas the interdecadal signals are driven mainly by the wind curl off the equatorial Pacific,which is closely related to the Pacific Decadal Oscillation.     

Re-calibration of Arctic sea ice extent datasets using Arctic surface air temperature records

A new seasonal and annual dataset describing Arctic sea ice extents for 1901–2015 was constructed by individually re-calibrating sea ice data sources from the three Arctic regions (North American, Nordic and Siberian) using the corresponding surface air temperature trends for the pre-satellite era (1901–1978), so that the strong relationship between seasonal sea ice extent and surface air temperature observed for the satellite era (1979-present) also applies to the pre-satellite era. According to this new dataset, the recent period of Arctic sea ice retreat since the 1970s followed a period of sea ice growth after the mid-1940s, which in turn followed a period of sea ice retreat after the 1910s. Arctic sea ice is a key component of the Arctic hydrological cycle, through both its freshwater storage role and its influence on oceanic and atmospheric circulation. Therefore, these new insights have significance for our understanding of Arctic hydrology.

EDITOR D. Koutsoyiannis

ASSOCIATE EDITOR not assigned     

Sea ice thickness measurement and its underside morphology analysis using radar penetration in the Arctic Ocean

Sea ice, as an important component of the Arctic climate system, has drawn significant sci-entific interest. Sea ice thickness and its morphology have dramatic impacts on ocean-atmos- phere-ice interactions[1—4], which directly affect the exchange proces…     

2002年南海季风爆发前后西沙海区海-气通量交换及其变化

利用2002年4月24日至6月20日在西沙海区进行的第三次南海海-气通量观测试验资料,采用涡相关法和TOGA COARE25b版本通量计算方案,计算了西南季风爆发前后海洋-大气间的通量交换,讨论了辐射、动量、感热通量、潜热通量、海洋热量净收支的时间变化特征及其与气象要素变化的关系.结果表明：西南季风爆发前后,太阳短波辐射、海面净辐射、潜热通量和海洋热量净收支变化特别强烈;通量变化受不同环境要素的影响：感热通量与海-气温差呈正相关关系,与气温呈明显的负相关关系.潜热通量与风速、海-气温差及海面水温均有正相关关系,其中与风速的关系最密切.动量通量（τ）主要随风速变化,它与风速（V）的关系可以表示为τ=000185V2-000559V+001248.     

An examination of snow redistribution over smooth land‐fast sea ice

An understanding of temporal evolution of snow on sea ice at different spatial scales is essential for improvement of snow parameterization in sea ice models. One of the problems we face, however, is that long‐term climate data are routinely available for land and not for sea ice. In this paper, we examine the temporal evolution of snow over smooth land‐fast first‐year sea ice using observational and modelled data. Changes in probability density functions indicate that depositional and drifting events control the evolution of snow distribution. Geostatistical analysis suggests that snowdrifts increased over the study period, and the orientation was related to the meteorological conditions. At the microscale, the temporal evolution of the snowdrifts was a product of infilling in the valleys between drifts. Results using two shore‐based climate reporting stations (Paulatuk and Tuktoyuktuk, NWT) suggest that on‐ice air temperature and relative humidity can be estimated using air temperature recorded at either station. Wind speed, direction and precipitation on ice cannot be accurately estimated using meteorological data from either station. The temporal evolution of snow distribution over smooth land‐fast sea ice was modelled using SnowModel and four different forcing regimes. The results from these model runs indicate a lack of agreement between observed distribution and model outputs. The reasons for these results are lack of meteorological measurements prior to the end of January, lack of spatially adequate surface topography and discrepancies between meteorological variables on land and ice. Copyright © 2009 John Wiley & Sons, Ltd.     

A finite element sea ice model of the Canadian Arctic Archipelago

The Canadian Arctic Archipelago (CAA) is a complex area formed by narrow straits and islands in the Arctic. It is an important pathway for freshwater and sea-ice transport from the Arctic Ocean to the Labrador Sea and ultimately to the Atlantic Ocean. The narrow straits are often crudely represented in coupled sea-ice–ocean models, leading to a misrepresentation of transports through these straits. Unstructured meshes are an alternative in modelling this complex region, since they are able to capture the complex geometry of the CAA. This provides higher resolution in the flow field and allows for more accurate transports (but not necessarily better modelling). In this paper, a finite element sea-ice model of the Arctic region is described and used to estimate the sea-ice fluxes through the CAA. The model is a dynamic–thermodynamic sea-ice model with elastic–viscous–plastic rheology and is coupled to a slab ocean, where the temperature and salinity are restored to climatology, with no velocities and surface elevation. The model is spun-up from 1973 to 1978 with NCEP/NARR reanalysis data. From 1979 to 2007, the model is forced by NCEP/DoE reanalysis data. The large scale sea-ice characteristics show good agreement with observations. The total sea-ice area agrees very well with observations and shows a sensitivity to the Arctic oscillation (AO). For 1998–2002, we find estimates for the sea-ice volume and area fluxes through Admunsen Gulf, McClure Strait and the Queen Elizabeth Islands that compare well with observation and are slightly better than estimates from other models. For Nares Strait, we find that the fluxes are much lower than observed, due to the missing effect of topographic steering on the atmospheric forcing fields. The 1979–2007 fluxes show large seasonal and interannual variability driven primarily by variability in the ice velocity field and a sensitivity to the AO and other large-scale atmospheric variability, which suggests that accurate atmospheric forcing might be crucial to modelling the CAA.     

Variability of dense water formation in the Ross Sea

This paper presents results from a model study of the interannual variability of high salinity shelf water (HSSW) properties in the Ross Sea. Salinity and potential temperature of HSSW formed in the western Ross Sea show oscillatory behaviour at periods of 5–6 and 9 years superimposed on long-term fluctuations. While the shorter oscillations are induced by wind variability, variability on the scale of decades appears to be related to air temperature fluctuations. At least part of the strong decrease of HSSW salinities deduced from observations for the period 1963–2000 is shown to be an aliasing artefact due to an undersampling of the periodic signal. While sea ice formation is responsible for the yearly salinity increase that triggers the formation of HSSW, interannual variability of net freezing rates hardly affects changes in the properties of the resulting water mass. Instead, results from model experiments indicate that the interannual variability of dense water characteristics is predominantly controlled by variations in the shelf inflow through a sub-surface salinity and a deep temperature signal. The origin of the variability of inflow characteristics to the Ross Sea continental shelf can be traced into the Amundsen and Bellingshausen Seas. The temperature anomalies are induced at the continental shelf break in the western Bellingshausen Sea by fluctuations of the meridional transport of circumpolar deep water with the eastern cell of the Ross Gyre. In the Amundsen Sea, upwelling due to a persistently cyclonic wind field carries the signal into the surface mixed layer, leading to fluctuations of the vertical heat flux, anomalies of brine release near the sea ice edge, and consequently to a sub-surface salinity anomaly. With the westward flowing coastal current, both the sub-surface salinity and deep temperature signals are advected onto the Ross Sea continental shelf. Convection carries the signal of salinity variability into the deep ocean, where it interacts with modified circumpolar deep water upwelled onto the continental shelf as the second source water mass of HSSW. Sea ice formation on the Ross Sea continental shelf thus drives the vertical propagation of the signal rather than determining the signal itself.     

Arctic sea ice thickness variations from CryoSat-2 satellite altimetry data

Arctic sea ice plays an important role in Earth's climate and environmental system. Sea ice thickness is one of the most important sea ice parameters. Accurately obtaining the sea ice thickness and its changes has great significance to Arctic and global change research. Satellite altimeters can be used to derive long-term and large-scale changes in sea ice thickness. The leads detection is vital in sea ice thickness estimation by using satellite altimetry. Different leads detection methods are compared with remote sensing images, and results show that the detection method that uses waveform parameters can obtain improved results. The model for the conversion of freeboard to thickness is optimized by considering the incomplete penetration of snow for radar altimeters. We derive the estimates of the Arctic sea ice thickness for November 2010 to December 2019 by using the CryoSat-2 altimetry data. The sea ice thickness from the IceBridge and draft data from the upward-looking sonar are used to validate our thickness results. Validations show that the accuracy of our thickness estimates is within 0.2 m. Variations in the Arctic sea ice thickness are analyzed using the PIOMAS model and air and sea surface temperatures. A sharp increase in sea ice thickness is found in 2014.